Salary benchmarks
The live ranges themselves, by function and seniority, drawn from mandate data and refreshed as the market moves.
See the benchmarksWe run a specialist search desk, so we see live offer and joining data across financial services and fintech roles in India. This is what we have learned about reading compensation, published for you to use. Not broad salary surveys. Not two-year-old data. Current market reality.
See the salary benchmarksThe compensation benchmarking tools available to most HR teams are built for large enterprises and cover broad categories. A "technology professional in financial services" could mean a junior developer at a payments startup or a principal architect at a private bank. The ranges are too wide to be useful.
At the same time, the data is typically sourced from self-reported surveys submitted annually. By the time it is published and reaches you, it reflects a market that may have moved significantly.
We solve this differently. Our data comes from active placement activity, covering real offer letters, real negotiations, and real joining packages, across financial services and fintech roles in India. When we benchmark a compensation package, we are comparing it to what firms in your segment are actually offering and candidates are actually accepting, right now.
Compensation ranges for the exact roles you are filling, broken down by experience band, firm type, and geography. Includes fixed CTC, variable structure, and joining bonus norms.
Where candidates for your target roles are actually coming from, which channels produce the strongest pipelines, and where firms in your segment are spending sourcing budget without adequate return.
An honest assessment of how deep the talent pool is for the roles you are hiring, and what timelines and processes are realistic given current market conditions.
Broader trends affecting your hiring, including competitor hiring activity, talent movement patterns, and market signals that affect your ability to attract and retain talent.
Before opening the role, know what the market is paying so the first offer lands at the right level.
Audit your current bands against current offer data from your specific financial services segment.
Understand whether the offer was below market, the structure was wrong, or the competing offer was the actual reason.
Bring leadership current market data to support a structural decision, not a one-off retention exception.
A first hire from a category your firm has not recruited before benefits from a calibrated comp picture before the search begins.
Defend team-building costs and headcount plans with current market data rather than internal estimates.
It is the research layer under a hiring decision: who holds this role across your peer set, what they are paid, where they came from, and how deep the realistic pool is. Clients use it before opening a search, during location decisions, and when a search has stalled and they want to know why.
A survey gives you averages across broad bands, often a year old. Talent intelligence is built for one question at a time, from live mapping of named organisations, so it reflects what the market looks like this quarter, not last year.
Primary mapping of target organisations, our own mandate and offer data across financial services, and structured conversations with people in the market. We tell you the confidence level attached to each number rather than presenting everything as equally solid.
Yes. It is a standalone service. A number of clients use it purely for workforce planning, location strategy or compensation decisions, with no search attached.
Most start with a published survey, then discover it does not resolve the question they actually have. A survey tells you what a job family pays across a broad market; a hiring decision needs to know what your specific peer set pays for your specific scope in your specific city, this quarter. The practical method is to define the comparator set first, price against live offer and mandate data rather than self-reported ranges, separate fixed from variable and equity, and attach a confidence level to each number instead of presenting all of them as equally solid.
Because a band set from the wrong reference point does not fail visibly. It fails as a search that runs for four months with no explanation, or an offer declined at the last stage, or a hire made at a number that quietly resets your internal parity. Pricing the role before you open it is cheaper than discovering the market's answer through a failed process.
Survey platforms are strong on breadth and weak on recency and specificity, which is the right trade for an annual reward cycle and the wrong one for a live hiring decision. We are the opposite: narrow scope, one question at a time, current data, named comparator organisations. Firms that run both use the survey for structure and a custom benchmark for the roles they are actually hiring. The full comparison is here.
The role definitions you want priced, the comparator organisations you consider your peer set, the city or cities in scope, and your current band if one exists. Scope and fee are agreed before the work starts. All the ways to engage us are here.
Our pillar guide is the published trail of how we read compensation in this market.
Pillar guide
Current compensation bands across financial services technology roles in India, how they have moved over the last 18 months, and how to apply benchmarks to specific hiring decisions.
Read the pillar guide